Derivation and Validation of a Geriatric‐Sensitive Perioperative Cardiac Risk Index. Issue 11 (15th November 2017)

• Record Type: Journal Article
• Authors: Alrezk, Rami; Jackson, Nicholas; Al Rezk, Mohanad; Elashoff, Robert; Weintraub, Nancy; Elashoff, David; Fonarow, Gregg C.
• Is Part Of: Journal of the American Heart Association. Volume 6:Issue 11(2017)
• Page Start: n/a
• Page End: n/a
• Publication Date: 2017-11-15
• Subjects: geriatrics -- myocardial infarction -- perioperative risk model -- risk prediction -- risk stratification -- surgery; Heart -- Diseases -- Periodicals; Cardiovascular system -- Diseases -- Periodicals; Cerebrovascular disease -- Periodicals; Cardiology -- Periodicals; 616.1
• DOI: 10.1161/JAHA.117.006648
• Languages: English
• ISSNs: 2047-9980

Abstract

Abstract : Background: Surgical patients aged 65 and over face a higher risk of cardiac complications from noncardiac surgery. The Revised Cardiac Risk Index (RCRI) and the Gupta Myocardial Infarction or Cardiac Arrest (MICA) calculator are widely used to predict this risk, but they are not specifically designed to predict MICA in geriatric patients. Our hypothesis is that a new geriatric‐sensitive index, derived from geriatric data, will capture this population's unique response to risk factors. Methods and Results: The model was developed using the NSQIP (National Surgical Quality Improvement Program) 2013 geriatric cohort (N=584, 931) (210, 914 age ≥65) and validated on the NSQIP 2012 geriatric cohort (N= 485, 426) (172, 905 age ≥65). Least Angle Shrinkage and Selection Operator regression was used for initial variable selection. The Geriatric‐Sensitive Cardiac Risk Index (GSCRI) was then evaluated in the 2012 data set. The area under the curve (AUC) was compared among the GSCRI, RCRI, and Gupta MICA in the 2012 data set. The GSCRI had an AUC of 0.76 in the validation cohort among geriatric patients. When the Gupta MICA was tested on geriatric patients in the validation cohort, a significant deterioration (≈17%) was noted, as well as a significant underestimation of the risk. The GSCRI AUC of 0.76 in the geriatric subset was significantly greater ( P <0.001) than those in the RCRI (AUC=0.63) or Gupta MICA (AUC=0.70) models, outperforming the RCRI and Gupta MICA models in geriatric patients by 13% and 6%, respectively, with a ΔAUC and P ‐value of 0.13 ( P <0.001), and 0.06 ( P <0.001). Conclusions: The GSCRI is a significantly better predictor of cardiac risk in geriatric patients undergoing noncardiac surgery.